Fault Diagnosis of Central Rigid Body-Flexible Manipulator Based on Iterative Learning Control

This paper investigates the fault diagnosis problem of a central rigid body-flexible manipulator, considers actuator faults, and designs an iterative learning-based fault estimator and fault learning algorithm for a central rigid body-flexible manipulator system. The fault diagnosis strategy proposed in this paper is divided into two parts: in the first part, the fault estimator is utilized to track out the fault information of the actuator. In the second part, the estimated fault information is fed back to the faulty actuator to compensate the fault signal in order to minimize the effect of the fault signal on the actuator. Finally, the effectiveness of the fault diagnosis strategy is verified by numerical simulation.